34 citations · 37 across the 5 of their papers we have counts for
7 papers
Super-Exponential Advantage of Squeezed Light in Phase Estimation under Discrete Phase Randomisation
Lorcan O. Conlon, V Vijendran, Aritra Das +7
A paradigmatic task in quantum metrology is that of phase estimation. For this task it is commonly believed, under reasonable assumptions about prior information, that a quadratic…
Deciding the Attainability of the Multiparameter Quantum Fisher Information is NP-Hard
Lorcan O. Conlon, Laura Shou, V Vijendran +7
The quantum Fisher information (QFI) sets a fundamental bound on the attainable precision when estimating multiple parameters simultaneously. Incompatibility among the individually…
Classical and Quantum Heuristics for the Binary Paint Shop Problem
V Vijendran, Dax Enshan Koh, Ping Koy Lam +1
The Binary Paint Shop Problem (BPSP) is an -hard optimisation problem arising in automotive manufacturing: given a sequence of cars, comprising distinct mode…
Automating Experimental Optics with Sample Efficient Machine Learning Methods
Arindam Saha, Baramee Charoensombutamon, Thibault Michel +7
As free-space optical systems grow in scale and complexity, troubleshooting becomes increasingly time-consuming and, in the case of remote installations, perhaps impractical. An ex…
Near-Optimal Parameter Tuning of Level-1 QAOA for Ising Models
V Vijendran, Dax Enshan Koh, Eunok Bae +3
The Quantum Approximate Optimisation Algorithm (QAOA) tackles combinatorial optimisation problems by encoding their solutions into the ground state of an Ising Hamiltonian prepared…
Modified Recursive QAOA for Exact Max-Cut Solutions on Bipartite Graphs: Closing the Gap Beyond QAOA Limit
Eunok Bae, Hyukjoon Kwon, V Vijendran +1
Quantum Approximate Optimization Algorithm (QAOA) is a quantum-classical hybrid algorithm proposed with the goal of approximately solving combinatorial optimization problems such a…
An Expressive Ansatz for Low-Depth Quantum Approximate Optimisation
V. Vijendran, Aritra Das, Dax Enshan Koh +2
The quantum approximate optimisation algorithm (QAOA) is a hybrid quantum-classical algorithm used to approximately solve combinatorial optimisation problems. It involves multiple…